1. Technical Field
The present invention relates generally to an apparatus and method for processing the data of heterogeneous sensors in an integrated manner to classify objects on a road and detect the locations of the objects and, more particularly, to an apparatus and method for processing the data of heterogeneous sensors in an integrated manner to classify objects on a road and detect the locations of the objects, which are capable of classifying objects on a road and also detecting the locations of the objects using heterogeneous sensors, that is, cameras and laser scanners, installed on the sides of the road.
2. Description of the Related Art
With the development of an Intelligent Transport System (ITS), roads have been gradually intellectualized. As part of this trend, road monitoring cameras, such as Closed-Circuit Television (CCTV) cameras and image detectors, have been widely installed and popularized to monitor vehicles and pedestrians on roads. Recently, a variety of methods have been proposed, such as a method of tracking and classifying vehicles using laser scanner sensors and then providing information to drivers or supporting autonomous driving.
Up to the present, a method of detecting vehicles on roads using cameras, such as CCTV cameras, has been chiefly used to monitor roads. As an example, Korean Patent Application Publication No. 10-2011-0099992 entitled “Real-time Traffic Situation Detection System” is configured to analyze the speed, type and traffic of vehicles by analyzing images captured using road image cameras installed on roads, bridges and/or tunnels and store an image when the analyzed information indicates that a situation has suddenly occurred.
As described above, CCTV cameras have the advantage of readily fulfilling multiple traffic lane, multiple detection requirements. However, existing detection technology using image cameras has the following problems. Since image cameras are installed in diagonal directions, an occlusion problem inevitably occurs. In order to solve this problem, image cameras are installed using tall poles. Nevertheless, the occlusion problem still remains. When traffic is not smooth, as in traffic congestion, vehicles are occluded and thus it is difficult to acquire information about the locations and speeds of vehicles. Furthermore, image cameras are sensitive to environmental factors, such as a tremendous snowfall, a heavy rainfall, day, and night and the reliability of classification and location estimation may be low because of the deterioration of image quality. A reflection effect may be generated by a road surface as in the case of the presence of a water film, erroneous detection is generated by the reflected light of a headlight, speed measurement errors occur, and erroneous detection is generated by a shadow.
In order to mitigate the above problems, laser scanners are installed on the sides of roads, so that the rate of classification of objects, such as vehicles, pedestrians and obstacles, can be increased and accurate location information can be obtained. Laser scanners are sensors that detect objects using distance values obtained using the reflection of light. Existing laser scanners are installed on vehicles, are configured to detect objects in front of, behind and beside the vehicles and calculate distance values, and are used in unmanned autonomous vehicles.
When such laser scanners are installed on the sides of roads or intersections, there are the advantages of rapidly detecting facilities, moving vehicles, pedestrians and obstacles on roads in real time from fixed locations where the laser scanners are installed and detecting accurate distances. Nevertheless, occluded objects are inevitably detected depending on the scan angle. There is a need for a method that mitigates this problem.